Showing 233 open source projects for "benchmark software"

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  • 1
    Benchmark

    Benchmark

    A microbenchmark support library

    A library to benchmark code snippets, similar to unit tests.
    Downloads: 0 This Week
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  • 2
    hyperfine

    hyperfine

    A command-line benchmarking tool

    A command-line benchmarking tool. Statistical analysis across multiple runs. Support for arbitrary shell commands. Constant feedback about the benchmark progress and current estimates. Warmup runs can be executed before the actual benchmark. Cache-clearing commands can be set up before each timing run. Statistical outlier detection to detect interference from other programs and caching effects. Export results to various formats: CSV, JSON, Markdown, AsciiDoc. Parameterized benchmarks (e.g....
    Downloads: 0 This Week
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  • 3
    BenchmarkTools.jl

    BenchmarkTools.jl

    A benchmarking framework for the Julia language

    BenchmarkTools makes performance tracking of Julia code easy by supplying a framework for writing and running groups of benchmarks as well as comparing benchmark results. This package is used to write and run the benchmarks found in BaseBenchmarks.jl. The CI infrastructure for automated performance testing of the Julia language is not in this package but can be found in Nanosoldier.jl. Our story begins with two packages, "Benchmarks" and "BenchmarkTrackers". The Benchmarks package...
    Downloads: 0 This Week
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  • 4
    kube-bench

    kube-bench

    Checks whether Kubernetes is deployed

    kube-bench is a tool that checks whether Kubernetes is deployed securely by running the checks documented in the CIS Kubernetes Benchmark. Trivy, the all-in-one cloud-native security scanner, can be deployed as a Kubernetes Operator inside a cluster. Both, the Trivy CLI, and the Trivy Operator support CIS Kubernetes Benchmark scanning among several other features. There are multiple ways to run kube-bench. You can run kube-bench inside a pod, but it will need access to the host's PID...
    Downloads: 3 This Week
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  • Gemini 3 and 200+ AI Models on One Platform Icon
    Gemini 3 and 200+ AI Models on One Platform

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  • 5
    Crow Framework

    Crow Framework

    A Fast and Easy to use microframework for the web

    A Fast and Easy to use microframework for the web. Crow is a C++ framework for creating HTTP or Websocket web services. It uses routing similar to Python's Flask which makes it easy to use. It is also extremely fast, beating multiple existing C++ frameworks as well as non-C++ frameworks. Crow is provided free of charge courtesy of everyone who is donating their money, time, and expertise to keep it going. The 1000-mile journey begins with a single step. Get started by installing Crow and...
    Downloads: 20 This Week
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  • 6
    Drill

    Drill

    Drill is an HTTP load testing application written in Rust

    Drill is an HTTP load-testing application written in Rust. The main goal for this project is to build a really lightweight tool as an alternative to other that require JVM and other stuff. You can write benchmark files, in YAML format, describing all the stuff you want to test. It was inspired by Ansible syntax because it is really easy to use and extend. As you can see, you can play with interpolations in different ways. This will let you specify a benchmark with different requests and...
    Downloads: 1 This Week
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  • 7
    JMH Gradle Plugin

    JMH Gradle Plugin

    Integrates the JMH benchmarking framework with Gradle

    The JMH Gradle Plugin provides integration of the Java Microbenchmark Harness (JMH) into Gradle builds, enabling developers to write and run performance benchmarks directly in their projects. JMH is the de facto standard for writing accurate and reliable Java microbenchmarks, and this plugin automates tasks like generating benchmark sources, compiling them with the required JMH support classes, and packaging runnable benchmark jars. It simplifies the workflow by handling classpath setup and...
    Downloads: 1 This Week
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  • 8
    SDGym

    SDGym

    Benchmarking synthetic data generation methods

    The Synthetic Data Gym (SDGym) is a benchmarking framework for modeling and generating synthetic data. Measure performance and memory usage across different synthetic data modeling techniques – classical statistics, deep learning and more! The SDGym library integrates with the Synthetic Data Vault ecosystem. You can use any of its synthesizers, datasets or metrics for benchmarking. You also customize the process to include your own work. Select any of the publicly available datasets from the...
    Downloads: 0 This Week
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  • 9
    LZ4

    LZ4

    Extremely fast compression algorithm

    ...It features an extremely fast decoder, with speed in multiple GB/s per core (~1 Byte/cycle). A high compression derivative, called LZ4_HC, is available, trading customizable CPU time for compression ratio. LZ4 library is provided as open-source software using a BSD license. This benchmark simulates simple "static content transfer" scenario such as OS Kernel compression or video game's static assets (text/images/tables/scripts/etc) which loading from Flash Memory / HDD / SSD. In this case, compression time is completely ignored. Because only content developers compress the data at once and usually they don't care about its computational cost. ...
    Downloads: 443 This Week
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  • 10
    golang-set

    golang-set

    A simple generic set type for the Go language

    A simple generic set type for the Go language. Trusted by Docker, 1Password, Ethereum and Hashicorp. The missing generic set collection for the Go language. Until Go has sets built-in...use this. One common interface to both implementations, a nonthreadsafe implementation favoring performance, a threadsafe implementation favoring concurrent use. Feature complete set implementation modeled after Python's set implementation. Exhaustive unit-test and benchmark suite. This package is trusted by...
    Downloads: 1 This Week
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  • 11
    Mitata

    Mitata

    benchmark tooling that loves you

    A high-performance JavaScript benchmarking tool designed for fast and accurate performance testing.
    Downloads: 0 This Week
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  • 12
    Recursive Language Models

    Recursive Language Models

    General plug-and-play inference library for Recursive Language Models

    RLM (short for Reinforcement Learning Models) is a modular framework that makes it easier to build, train, evaluate, and deploy reinforcement learning (RL) agents across a wide range of environments and tasks. It provides a consistent API that abstracts away many of the repetitive engineering patterns in RL research and application work, letting developers focus on modeling, experimentation, and fine-tuning rather than infrastructure plumbing. Within the framework, you can define custom...
    Downloads: 1 This Week
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  • 13
    Image Harmonization Dataset iHarmony4

    Image Harmonization Dataset iHarmony4

    The first large-scale public benchmark dataset for image harmonization

    This repository provides the iHarmony4 dataset, which is a large-scale dataset designed for image harmonization tasks. Image harmonization involves adjusting the appearance of a foreground in a composite image so that it is consistent with the background (in color, tone, illumination, etc.). The iHarmony4 dataset comprises four sub-datasets (HCOCO, HAdobe5k, HFlickr, Hday2night), each making composite images by combining a foreground from one image with a background from another, along with...
    Downloads: 2 This Week
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  • 14
    plow

    plow

    A high-performance HTTP benchmarking tool

    Plow is an HTTP(S) benchmarking tool, written in Golang. It uses excellent fast HTTP instead of Go's default net/http due to its lightning-fast performance. Plow runs at specified connections (option -c) concurrently and real-time records summary statistics, histogram of execution time and calculates percentiles to display on Web UI and terminal. It can run for a set duration( option -d), for a fixed number of requests(option -n), or until Ctrl-C is interrupted. The implementation of...
    Downloads: 2 This Week
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  • 15
    pnpm

    pnpm

    Fast, disk space efficient package manager

    Fast, disk space efficient package manager. pnpm uses a content-addressable filesystem to store all files from all module directories on a disk. When using npm, if you have 100 projects using lodash, you will have 100 copies of lodash on disk. With pnpm, lodash will be stored in a content-addressable storage. Files inside node_modules are cloned or hard-linked from a single content-addressable storage. pnpm has built-in support for multiple packages in a repository. pnpm creates a non-flat...
    Downloads: 25 This Week
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  • 16
    NYC Taxi Data

    NYC Taxi Data

    Import public NYC taxi and for-hire vehicle (Uber, Lyft)

    The nyc-taxi-data repository is a rich dataset and exploratory project around New York City taxi trip records. It collects and preprocesses large-scale trip datasets (fares, pickup/dropoff, timestamps, locations, passenger counts) to enable data analysis, modeling, and visualization efforts. The project includes scripts and notebooks for cleaning and filtering the raw data, memory-efficient processing for large CSV/Parquet files, and aggregation workflows (e.g. trips per hour, heatmaps of...
    Downloads: 1 This Week
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  • 17
    PyTorch Geometric

    PyTorch Geometric

    Geometric deep learning extension library for PyTorch

    It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of an easy-to-use mini-batch loader for many small and single giant graphs, a large number of common benchmark datasets (based on simple interfaces to create your own), and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds. We have outsourced a lot of...
    Downloads: 1 This Week
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  • 18
    Pythonic Data Structures and Algorithms

    Pythonic Data Structures and Algorithms

    Minimal examples of data structures and algorithms in Python

    The Pythonic Data Structures and Algorithms repository by keon is a hands-on collection of implementations of classical data structures and algorithms written in Python. It offers working, often well-commented code for many standard algorithmic problems — from sorting/searching to graph algorithms, dynamic programming, data structures, and more — making it a valuable resource for learning and reference. For students preparing for technical interviews, self-learners brushing up on...
    Downloads: 4 This Week
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  • 19
    Python Outlier Detection

    Python Outlier Detection

    A Python toolbox for scalable outlier detection

    PyOD is a comprehensive and scalable Python toolkit for detecting outlying objects in multivariate data. This exciting yet challenging field is commonly referred as outlier detection or anomaly detection. PyOD includes more than 30 detection algorithms, from classical LOF (SIGMOD 2000) to the latest COPOD (ICDM 2020) and SUOD (MLSys 2021). Since 2017, PyOD [AZNL19] has been successfully used in numerous academic researches and commercial products [AZHC+21, AZNHL19]. PyOD has multiple neural...
    Downloads: 0 This Week
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  • 20
    AlphaZero.jl

    AlphaZero.jl

    A generic, simple and fast implementation of Deepmind's AlphaZero

    Beyond its much publicized success in attaining superhuman level at games such as Chess and Go, DeepMind's AlphaZero algorithm illustrates a more general methodology of combining learning and search to explore large combinatorial spaces effectively. We believe that this methodology can have exciting applications in many different research areas. Because AlphaZero is resource-hungry, successful open-source implementations (such as Leela Zero) are written in low-level languages (such as C++)...
    Downloads: 33 This Week
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  • 21
    Apache Sedona

    Apache Sedona

    Cluster computing framework for processing large-scale geospatial data

    Apache Sedona™ is a cluster computing system for processing large-scale spatial data. Sedona extends existing cluster computing systems, such as Apache Spark and Apache Flink, with a set of out-of-the-box distributed Spatial Datasets and Spatial SQL that efficiently load, process, and analyze large-scale spatial data across machines. According to our benchmark and third-party research papers, Sedona runs 2X - 10X faster than other Spark-based geospatial data systems on computation-intensive...
    Downloads: 0 This Week
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  • 22
    chinese-independent-developer

    chinese-independent-developer

    List of independent developer projects in China

    ...It also acts as a historical snapshot of the Chinese indie dev ecosystem, preserving projects even after they have stopped active development. For new indie creators, the list works as inspiration and a benchmark, illustrating a spectrum of product ideas, niches, and business models that others have tried.
    Downloads: 2 This Week
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  • 23
    youki

    youki

    A container runtime written in Rust

    youki is an implementation of the OCI runtime-spec in Rust, similar to runc. Rust is one of the best languages to implement the oci-runtime spec. Many very nice container tools are currently written in Go. However, the container runtime requires the use of system calls, which requires a bit of special handling when implemented in Go. This is too tricky (e.g. namespaces(7), fork(2)); with Rust, it's not that tricky. And, unlike in C, Rust provides the benefit of memory safety. While Rust is...
    Downloads: 1 This Week
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  • 24
    TextDistance

    TextDistance

    Compute distance between sequences

    Python library for comparing the distance between two or more sequences by many algorithms. For main algorithms, text distance try to call known external libraries (fastest first) if available (installed in your system) and possible (this implementation can compare this type of sequences). Install text distance with extras for this feature. Textdistance use benchmark results for algorithm optimization and try to call the fastest external lib first (if possible). TextDistance show benchmarks...
    Downloads: 0 This Week
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  • 25
    PlatEMO

    PlatEMO

    Evolutionary multi-objective optimization platform

    Evolutionary multi-objective optimization platform. PlatEMO consists of a number of MATLAB functions without using any other libraries. Any machines able to run MATLAB can use PlatEMO regardless of the operating system. PlatEMO includes more than ninety existing popular MOEAs, including genetic algorithm, differential evolution, particle swarm optimization, memetic algorithm, estimation of distribution algorithm, and surrogate model-based algorithm. Most of them are representative algorithms...
    Downloads: 1 This Week
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